摘要
随着城市化进程的快速推进,超大城市交通系统的规模与复杂性呈指数级增长,对精细化交通治理提出了迫切需求。城市道路智能化全息测绘技术通过融合车载激光扫描、地面固定站观测、多源遥感等异构数据,构建出道路全要素、高精度、时空一体化的信息采集体系,为超大城市交通规划、设施运维及应急管理提供核心数据支持。本文系统梳理该技术的多源数据采集、时空基准统一、全息要素语义提取等关键技术构成,结合上海超大城市的应用实践,深入分析其在海量点云管理、动态更新机制等方面面临的挑战,并针对性地提出混合存储架构、分层级更新策略及智能化处理方案,旨在为推动城市道路智能化全息测绘技术在超大城市交通领域的规模化应用提供理论参考与实践路径,助力提升超大城市交通治理现代化水平。
With the rapid advancement of urbanization,the scale and complexity of transportation systems in megacities have grown exponentially,creating an urgent demand for refined traffic governance.Urban road intelligent holographic surveying technology integrates heterogeneous data from vehicle-mounted laser scanning,ground-based fixed-station observations,and multi-source remote sensing to establish a comprehensive,high-precision,spatiotemporal-integrated information acquisition system for road elements.This serves as core data support for transportation planning,infrastructure maintenance,and emergency management in megacities.This paper systematically reviews the key technical components of this technology,including multi-source data collection,spatiotemporal reference unification,and semantic extraction of holographic elements.By analyzing its application in Shanghai—a megacity case study—it delves into challenges such as massive point cloud management and dynamic update mechanisms,proposing targeted solutions like hybrid storage architectures,hierarchical update strategies,and intelligent processing schemes.The study aims to provide theoretical references and practical pathways for scaling the application of intelligent holographic surveying technology in megacity transportation,thereby advancing the modernization of traffic governance.
作者
万从容
孙悦
Wan Congrong;Sun Yue(Shanghai Municipal Institute of Surveying and Mapping,Shanghai 200063,China;Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities,Shanghai 200063,China)
出处
《工程勘察》
2026年第2期88-94,共7页
Geotechnical Investigation & Surveying
关键词
超大城市
智能化全息测绘
多源数据融合
城市精细化管理
点云数据管理
质量控制
megacity
intelligent holographic surveying
multi-source data fusion
urban refined management
point cloud data management
quality control
